As the ability to produce a large number of small, simple robotic agents improves, it becomes essential to control the behavior of these agents in such a way that the sum of their...
Despite the recent advances in planning with MDPs, the problem of generating good policies is still hard. This paper describes a way to generate policies in MDPs by (1) determiniz...
We dene the probabilistic planning problem in terms of a probability distribution over initial world states, a boolean combination of goal propositions, a probability threshold, ...
Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in largescale systems. In this work, we develop an organization-b...
Chongjie Zhang, Sherief Abdallah, Victor R. Lesser
We describe a Multi-Agent System (MAS) for controlling teams of uninhabited air vehicles (UAVs) in the context of a larger system that has been used to evaluate potential concepts...